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The power of prediction with social media

dc.contributor.authorSchoen, Harald
dc.contributor.authorGayo Avello, Daniel 
dc.contributor.authorMetaxas, Panagiotis T.
dc.contributor.authorMustafaraj, Eni
dc.contributor.authorStrohmaier, Markus
dc.contributor.authorGloor, Peter
dc.date.accessioned2014-03-14T07:43:15Z
dc.date.available2014-03-14T07:43:15Z
dc.date.issued2013
dc.identifier.citationInternet Research, 23(5), p. 528-543 (2013); doi:10.1108/IntR-06-2013-0115
dc.identifier.issn1066-2243
dc.identifier.urihttp://hdl.handle.net/10651/24088
dc.description.abstractSocial media provide an impressive amount of data about users and their interactions, thereby offering computer and social scientists, economists, and statisticians – among others – new opportunities for research. Arguably, one of the most interesting lines of work is that of predicting future events and developments from social media data. However, current work is fragmented and lacks of widely accepted evaluation approaches. Moreover, since the first techniques emerged rather recently, little is known about their overall potential, limitations and general applicability to different domains. Therefore, better understanding the predictive power and limitations of social media is of utmost importance
dc.description.sponsorshipThe work of P. Metaxas and E. Mustafaraj was supported by NSF grant CNS-117693.
dc.format.extentp. 528-543
dc.language.isoeng
dc.publisherEmerald
dc.relation.ispartofInternet Research, 23(5)
dc.rights© Emerald
dc.titleThe power of prediction with social mediaeng
dc.typeinfo:eu-repo/semantics/article
dc.identifier.local20140990
dc.identifier.doi10.1108/IntR-06-2013-0115
dc.type.dcmitext
dc.relation.publisherversionhttp://dx.doi.org/10.1108/IntR-06-2013-0115


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